
Engine Biosciences
Applying machine learning to genomics for drug discovery.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor investor investor | €0.0 | round |
N/A | €0.0 | round | |
investor investor investor investor investor investor | €0.0 | round | |
investor investor investor investor investor investor investor investor investor investor investor | €0.0 | round | |
investor investor | €0.0 Valuation: €0.0 | round | |
investor | €0.0 Valuation: €0.0 | round | |
* | $27.0m Valuation: $215m | Series A | |
Total Funding | 000k |
Related Content
Engine Biosciences is a biotechnology firm using machine learning and proprietary biological experimentation platforms to advance precision oncology. Founded in 2014 by Jeffrey Lu and Timothy Lu, the company operates from Singapore and Silicon Valley, aiming to accelerate and reduce the cost of drug discovery. Jeffrey Lu, the Co-Founder and CEO, has a background in building and leading various biotech and tech companies, including Enleofen Bio and AAE, after starting his career at Bain & Company. Timothy Lu, a co-founder, is a faculty member at MIT and has co-founded several other biotech companies, including Senti Biosciences and Synlogic.
The company has built a significant capital base, raising a total of $86 million across several funding rounds. This includes a $10 million seed round in 2018, an initial Series A round of $43 million, and a subsequent $27 million Series A extension in late 2023 led by Polaris Partners. These funds are directed towards expanding the company's drug discovery platform, advancing preclinical studies, and growing its scientific and executive teams.
Engine Biosciences' core technology rests on two main platforms: NetMAPPR® and CombiGEM. NetMAPPR is a machine learning-enabled platform that analyzes vast biological and patient datasets to identify critical gene interactions driving diseases. CombiGEM is a proprietary high-throughput experimental platform that uses combinatorial CRISPR screening to test and validate the predictions made by the AI. This integrated system of computational prediction followed by wet-lab validation allows the company to decipher complex biological networks, particularly focusing on the principle of synthetic lethality in oncology. The platform has identified over 30 novel precision medicine opportunities and biomarkers that can significantly increase tumor sensitivity to certain drugs.
The business model is centered on internal drug development and strategic partnerships. Engine Biosciences develops its own pipeline of therapeutics targeting cancers such as liver, ovarian, colorectal, and breast cancer. Simultaneously, it collaborates with pharmaceutical companies, biotech firms, academic institutions, and healthcare systems. These partnerships provide access to clinical trial networks, patient data, and specialized expertise, accelerating the path to market. A key collaboration was announced in April 2025 with Singapore's Experimental Drug Development Centre (EDDC) to co-develop first-in-class precision cancer treatments, starting with a program targeting cancers prevalent in Asia and globally.
Keywords: precision oncology, drug discovery, machine learning, synthetic lethality, network biomedicine, CRISPR screening, computational biology, functional genomics, therapeutic pipeline, biomarker discovery, oncology therapeutics, genetic interactions, drug development, biotech, cancer treatment, high-throughput screening, venture-backed, clinical development, patient selection biomarkers, targeted therapies, cancer research